Deep learning-based model for detection of intracranial waveforms with poor brain compliance in southernThailand

The DL-based model successfully detected pathological ICP waveforms, thereby enhancing clinical decision-making. As DL advances, its significance in neurocritical care will help to pave the way for more individualized and data-driven approaches to brain monitoring and management.

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Publication Details

Journal
Acute and Critical Care
Published
2025-08-29
DOI
https://doi.org/10.4266/acc.001425
Citations
1
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.84
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article

Deep learning-based model for detection of intracranial waveforms with poor brain compliance in southernThailand

Thara Tunthanathip, Avika Trakulpanitkit
1 citations
Acute and Critical Care
Brain Tumor Detection and Classification
0.84
article

Deep learning-based model for detection of intracranial waveforms with poor brain compliance in southernThailand

Thara Tunthanathip, Avika Trakulpanitkit
article en
1 citations

Abstract

The DL-based model successfully detected pathological ICP waveforms, thereby enhancing clinical decision-making. As DL advances, its significance in neurocritical care will help to pave the way for more individualized and data-driven approaches to brain monitoring and management.

Acute and Critical CareVol. 40(3)
Prince of Songkla University (TH)
Openalex Percentile: Top 22%
Brain Tumor Detection and Classification
0.84
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Deep learning-based model for detection of intracranial waveforms with poor brain compliance in southernThailand — Thara Tunthanathip, Avika Trakulpanitkit · Acute and Critical Care (2025) | TGRS Research Map | TGRS